We document the performance of a new earth system model developed at Korea Institute of Ocean Science and Technology, called the KIOST-ESM, based on a low-resolution (~ 200 km for the atmosphere, ~ 100 km for the ocean) version of the Geophysical Fluid Dynamics Laboratory Climate Model 2.5. The main changes made to the base model include adopting a unified convection scheme for cumulus convection and an ocean mixed layer parameterization considering Langmuir circulation, which improve the model fidelity significantly. In addition, the KIOST-ESM adopts a new soil respiration scheme in the dynamic vegetation process of its land component. The performance of the KIOST-ESM was assessed in pre-industrial and historical simulations that are made as part of its participation in the Coupled Model Intercomparison Project phase 6 (CMIP6). The response of the earth system to increasing greenhouse gas concentrations was analyzed in the ScenarioMIP simulations. An abrupt quadrupling of CO2 experiment suggests that the equilibrium climate sensitivity of KIOST-ESM is 3.36 K—very close to the averaged one obtained from CMIP5 simulations. Although the KIOST-ESM showed a notable cold bias in the Northern Hemisphere and the double Inter-Tropical Convergence Zone bias, the KIOST-ESM outperforms the base model in simulating the mean sea surface temperature over the Southern Ocean and over the cold tongue in the tropical Pacific. The KIOST-ESM can also simulate the dominant tropical variability in intraseasonal (Madden–Julian Oscillation) and interannual (El Niño-Southern Oscillation) timescales more realistically.
Bibliographical noteFunding Information:
We thank two anonymous reviewers for helping us to improve this manuscript. This work was supported by the National Research Foundation of Korea grant NRF‐2016M1A2A2948277 funded by the Korean government (MSIT) and the Ministry of Oceans and Fisheries, Korea (Investigation and prediction system development of marine heatwave around the Korean Peninsula originated from the subarctic and western Pacific, 20190344). G. Pak was supported by inhouse project of the Korea Institute of Ocean Science & Technology (PE99811&PE99911). Y.H. Kim was supported by the project titled ‘Improvements of ocean prediction accuracy using numerical modeling and artificial intelligence technology’, funded by the Ministry of Oceans and Fisheries, Korea.
© 2021, Korea Institute of Ocean Science & Technology (KIOST) and the Korean Society of Oceanography (KSO) and Springer Nature B.V.
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